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EvoScientist is an open-source framework that automates research workflows using self-evolving AI scientists with persistent multi-agent memory, adopting a human-on-the-loop paradigm for autonomous research exploration and insight generation.
The article explains how Manus's Browser Operator works by operating inside the user's authorized local browser session, allowing it to access subscription-based and authenticated content beyond typical AI search capabilities, and provides a step-by-step guide for enabling and using it.
Hugging Face replaced its post-training team with an autonomous agent that reads papers, runs GPU experiments, and improves models, achieving a 22-point benchmark jump in under 10 hours and beating Codex on HealthBench by 60%.
Andrej Karpathy's autoresearch pattern highlights how current AI agents run experiments in isolation, wasting compute by duplicating work and rediscovering dead ends.
The article argues that there is a high likelihood (60%+) of fully automated AI R&D—where AI systems can build their own successors without human involvement—by the end of 2028, citing evidence from coding benchmarks like SWE-Bench and trends in AI autonomy.